Exploring the evolution of red and blue galaxies in different cosmic web environments using IllustrisTNG simulation
arXiv:2410.23896 · doi:10.1088/1475-7516/2025/09/071
Abstract
We analyze the evolution of red and blue galaxies in different cosmic web environments from redshift to using the IllustrisTNG simulation. We use Otsu's method to classify the red or blue galaxies at each redshift and determine their geometric environments from the eigenvalues of the deformation tensor. Our analysis shows that initially, blue galaxies are more common in clusters followed by filaments, sheets and voids. However, this trend reverses at lower redshifts, with red fractions rising earlier in denser environments. At , most massive galaxies () are quenched across all environments. In contrast, low-mass galaxies () are more influenced by their environment, with clusters hosting the highest red galaxy fractions at low redshifts. We observe a slower mass growth for low-mass galaxies in clusters at . Filaments show relative red fractions (RRF) comparable to clusters at low masses, but host nearly of low-mass blue galaxies, representing a diverse galaxy population. It implies that less intense environmental quenching in filaments allows galaxies to experience a broader range of evolutionary stages. Despite being the densest environment, clusters display the highest relative blue fraction (RBF) for high-mass galaxies, likely due to interactions or mergers that can temporarily rejuvenate star formation in some of them. The colour distribution transitions from unimodal to bimodal by redshift across all environments. At , clusters exhibit the highest median colour and lowest median specific star formation rate (sSFR), with stellar mass being the primary driver of colour evolution in massive galaxies. Our study suggests that stellar mass governs quenching in high-mass galaxies, while a complex interplay of mass and environment shapes the evolution of low-mass galaxies.
arXiv comment33 pages, 20 figures, 3 tables, Revised the presentation and included an Appendix analyzing the influence of varying local density and filter width on the results, Accepted for publication in JCAP
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